Sales Prediction with Python involves forecasting product sales based on various influencing factors such as advertising expenditure, target audience segmentation, seasonality, and market trends. It uses machine learning techniques to analyze past data and predict future sales.

Key Features:

• Leverages data-driven insights for accurate sales forecasting.
• Incorporates multiple factors like advertisement spending, customer demographics, and market conditions.
• Supports techniques such as regression models and time-series analysis.

Skills Used:

• Data cleaning and preprocessing.
• Building and evaluating predictive models (e.g., Linear Regression, Decision Trees).
• Visualization of data trends using Python libraries like Matplotlib and Seaborn.
• Proficiency in Python frameworks such as Pandas, NumPy, and Scikit-learn.